The successful conduct of clinical trials requires an excellent collaboration between a Clinical Coordinating Center (CCC), a Data Coordinating Center (DCC), and the clinical sites where subjects are enrolled and followed. One would be hard pressed to find many examples of projects that succeeded in spite of poor relationships. However, developing successful collaborative relationships among diverse groups of individuals is a difficult and resource intensive process. The disproportionate amount of resources required to create de novo consortiums and cultivate new relationships is one limiting aspect of the common approach to conducting multi-center clinical trials. The Network of Excellence in Neuroscience Clinical Trials (NEXT) will provide common reusable resources that many clinical trials can leverage. This application requests funds to support the creation of a DCC at the University of Iowa. The DCC will support study design, data collection, data management, project management, clinical site monitoring, quality management, safety monitoring, and statistical aspects of the proposed trial. The specific aims of the DCC application are to: 1) Provide study design and statistical leadership; 2) Develop and maintain a web-based distributed data entry system with the capability to quickly, efficiently, and accurately randomize subjects and collect data generated by the studies conducted within the network; 3) Provide project management support for the studies conducted within the network; and 4) Provide access to study-wide and network information. The DCC will provide a robust, standardized, and accessible infrastructure to facilitate rapid development and implementation of protocols for conducting clinical trials in neuroscience. Additionally, the proposed DCC infrastructure is explicitly designed to accommodate dynamically changing requirements that naturally occur in clinical trials (both planned and unplanned). The proposed DCC will provide more rapid evaluation of promising treatments in neuroscience, and will be a model that can be replicated across a number of studies and diseases.